In recent years, there has been a significant motivation to develop software techniques for the noninvasive diagnosis of abnormal functioning of the vocal apparatus by studying the patients' voice signal. Learn about noninvasive pathology approaches for the prediction of healthy and affected voice signals from a recent Lecture Notes in the IEEE Signal Processing Magazine.

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In September 2009, USA Today and other media outlets have reported a successful servicing mission to the Hubble Space telescope. The In-the-Spotlight column in the January 2010 issue of the IEEE Signal Processing Magazine provided a closer look at the imaging sensors and the associated processing and control mechanisms in the Hubble and its successor.

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Polarimetric Synthetic Aperture Radar (POLSAR) data is an important source for many operational remote sensing applications. Segmentation and classification of image data are important tasks for POLSAR data analysis and interpretation, which often requires human interaction. In this thesis, spectral graph partitioning methodology is used to exploit both the polarimetric attributes of pixels, and the visual aspect of the image data through visual cues.

Signal processing engineers usually use high level languages to develop advanced algorithms for new radars and to determine the optimal parameters for these algorithms. The long execution times due to computational complexity and/or very large data sets hinders an efficient engineering development workflow. Rapid prototyping tools such as parallel MATLAB can enable a software design workflow that helps the development of radar prototypes by providing interactivity and reducing the execution time of the algorithms under test.